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Wells Fargo Logo Wells Fargo · IT - Software Development

Senior Lead AI Research Scientist – Foundation Models & Agentic AI

United States, Charlotte 185000.00 - 300000.00 USD / Year · Job Posted June 16, 2026
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Job Description

Wells Fargo’s Model Risk Management (MRM) team is seeking a Senior Lead Quantitative Analytics Specialist (AI Research Scientist Lead – Foundation Models & Agentic AI) to drive advanced AI initiatives. This role will lead the development and evaluation of next-generation Foundation Models, Agentic AI solutions, and Generative AI systems, ensuring they are robust, scalable, and aligned with regulatory expectations. This is a high-impact opportunity to operate at the intersection of AI innovation and model risk oversight, partnering with business, technology, and risk leaders to bring cutting-edge AI capabilities into real-world financial applications that serve millions of customers.

Job Responsibility

  • Lead end-to-end research projects in Agentic AI / AI / Generative AI / Machine Learning from ideation, research, experimentation, implementation, evaluation, transfer and documentation
  • Contribute and lead building the next generation of foundation models and agentic AI systems trained / operating on large volumes of heterogeneous data - both structured and unstructured - that enhance Wells Fargo's products, services, and operations
  • Lead the deployment of foundation models, LLMs, and agentic AI systems into production, with a strong understanding of deployment trade-offs
  • Drive the exploration, application, and rigorous evaluation of emerging AI technologies that solve real-world challenges
  • Collaborate closely with interdisciplinary teams, including researchers, data scientists, applied engineers, and domain experts
  • Translate research insights into impactful business solutions, open-source contributions, patents, and publications
  • Publish in top-tier AI/ML conferences and journals and represent Wells Fargo in the broader AI research community

Requirements

  • 7+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Nice to have

  • PhD in Computer Science, Artificial Intelligence, or a closely related computational field, or an MSc with at least 3 years of relevant applied research / research innovation or industry experience building foundational models
  • Solid proven research track record with publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP, combined with a demonstrated interest in translating research into real-world applications that impact millions of customers
  • Deep expertise in one or more specialized areas, including but not limited to: Foundation Models (GPT-4, BERT, LLaMA, Claude), Large Language Models (LLMs), Large Reasoning Models, Multimodal Models, Agentic AI
  • Demonstrated ability to apply GenAI / Agentic AI in the full build lifecycle - design, implementation, testing, and iteration - leveraging AI coding copilots (e.g., GitHub Copilot) and agentic coding workflows to accelerate delivery while maintaining enterprise standards
  • Hands-on experience with GPU infrastructure, Transformer architecture, modern AI/ML development frameworks and tools such as TensorFlow, PyTorch, Hugging Face, AWS, GCP
  • Strong engineering background with demonstrated ability to contribute to collaborative software engineering projects, including version control, code reviews, and scalable system design
  • Experience with transferring foundation models, LLMs, and agentic AI systems in production

What we offer

  • Health benefits
  • 401(k) Plan
  • Paid time off
  • Disability benefits
  • Life insurance, critical illness insurance, and accident insurance
  • Parental leave
  • Critical caregiving leave
  • Discounts and savings
  • Commuter benefits
  • Tuition reimbursement
  • Scholarships for dependent children
  • Adoption reimbursement
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